Executing cognitive automation testing

For successful testing and deployment of cognitive automation, we should always prepare an approach to testing. In this section, let's review details on gathering test data, executing RPA and cognitive tests, and tying it all together with executing UAT tests.

Gathering test data

ML depends highly on data. Having the right types and the right amount of data is crucial in having a successful ML model deployed; therefore, data preparation is such an important part of the ML process.

When gathering test data, many organizations ask how much data is necessary to get started. Unfortunately, there isn't an explicit answer to this question, as there are many variables that can affect how much data is necessary, such as the following:

• The complexity of the business problem ML must solve
• The number of classifications (if necessary)
• The complexity of the algorithm used

If necessary, you can try to target the...